Apache Cassandra is a popular NoSQL database because it is scalable and can be highly available with multi-datacenter replication. Cassandra can be used as a high performance solution for structured queries, but this requires that the data must be modeled such that each pre-defined query results in the retrieval of a single row of data. This pre-planning imposes severe limitations on Cassandra's use as it requires knowledge of all possible queries before modeling the data. Cassandra's performance also suffers because it stores data on disk and not in memory. Cassandra is also limited by:

Lack of an in-memory computing option

No support for transactions, ACID or otherwise

No SQL support and no ability to perform joins, aggregations, groupings or to build usable indexes

No ability to run ad hoc queries

However, inserting the GridGain In-Memory Data Fabric between Apache Cassandra and an application provides the following capabilities for the portion of the data stored in the GridGain In-Memory Data Fabric:

ANSI SQL-99 compliance to run ad hoc and structured queries

ACID compliant distributed transactions

A 1,000x or more query speed improvement by leveraging distributed in-memory computing architectures

Read-through and write-through data from and to Cassandra

For more in-depth information on GridGain’s integration with Apache Cassandra, please view this webinar and download this white paper.